Abstract

IgA Nephropathy (IgAN) is a worldwide disease that affects kidneys in human beings and leads to end-stage kidney disease (ESKD) thus requiring renal replacement therapy with dialysis or kidney transplantation. The need for new tools able to help clinicians in predicting ESKD risk for IgAN patients is highly recognized in the medical field. In this paper we present a software tool that exploits the power of artificial neural networks to classify patients’ health status potentially leading to ESKD. The classifier leverages the results returned by an ensemble of 10 networks trained by using data collected in a period of 38 years at University of Bari. The developed tool has been made available both as an online Web application and as an Android mobile app. Noteworthy to its clinical usefulness is that its development is based on the largest available cohort worldwide.

Autore Pugliese

• Di Noia Tommaso , Di Sciascio Eugenio , Naso David

Tutti gli autori

• Di Noia, Tommaso , Ostuni, Vito Claudio , Pesce, Francesco , Binetti, Giulio , Naso, David , Schena, Francesco Paolo , Di Sciascio, Eugenio

Titolo volume/Rivista

EXPERT SYSTEMS WITH APPLICATIONS

Anno di pubblicazione

2013

ISSN

0957-4174

ISBN

Non Disponibile

Numero di citazioni Wos

Nessuna citazione

Ultimo Aggiornamento Citazioni

Non Disponibile

Numero di citazioni Scopus

11

Ultimo Aggiornamento Citazioni

2017-04-23 03:20:56

Settori ERC

Non Disponibile

Codici ASJC

Non Disponibile